1. Field of the Invention
The present invention relates to devices and methods for measuring the concentration of one or more analytes in a biological sample. More specifically, this invention relates to devices and methods for the noninvasive determination of analyte concentrations in vivo, e. g., glucose concentrations in blood.
2. Discussion of the Art
Diabetes: Incidence, Effects and Treatment
Diabetes mellitus is a chronic disorder of carbohydrate, fat, and protein metabolism characterized by an absolute or relative insulin deficiency, hyperglycemia, and glycosuria. At least two major variants of the disease have been identified. xe2x80x9cType Ixe2x80x9d accounts for about 10% of diabetics and is characterized by a severe insulin deficiency resulting from a loss of insulin-secreting beta cells in the pancreas. The remainder of diabetic patients suffer from xe2x80x9cType IIxe2x80x9d, which is characterized by an impaired insulin response in the peripheral tissues (Robbins, S. L. et al., Pathologic Basis of Disease, 3rd Edition, W. B. Saunders Company, Philadelphia, 1984, p. 972). If uncontrolled, diabetes can result in a variety of adverse clinical manifestations, including retinopathy, atherosclerosis, microangiopathy, nephropathy, and neuropathy. In its advanced stages, diabetes can cause blindness, coma, and ultimately death.
The principal treatment for Type I diabetes is periodic insulin injection. Appropriate insulin administration can prevent, and even reverse, some of the adverse clinical outcomes for Type I diabetics. Frequent adjustments of the blood glucose level can be achieved either by discrete injections or, in severe cases, via an implanted insulin pump or artificial pancreas. The amount and frequency of insulin administration is determined by frequent or, preferably, continuous testing of the blood glucose level.
Tight control of blood glucose in the xe2x80x9cnormal rangexe2x80x9d, 60-120 mg/dL, is necessary for diabetics to avoid or reduce complications resulting from hypoglycemia and hyperglycemia. To achieve this level of control, the American Diabetes Association recommends that diabetics test their blood glucose 5 times per day. Thus, there is a need for accurate and frequent or, preferably, continuous glucose monitoring to combat the effects of diabetes.
Invasive Glucose Measurement
Conventional blood glucose measurements in a hospital or physician""s office rely on the withdrawal of a 5-10 ml blood sample for analysis. This method is slow and painful and cannot be used for continuous glucose monitoring. An additional problem for hospitals and physician offices is the disposal of testing elements that are contaminated by blood.
Implantable biosensors have also been proposed for glucose measurement. (G. S. Wilson, Y. Zhang, G. Reach, D. Moatti-Sirat, V. Poitout, D. R. Thevenot, F. Lemonnier, and J.-C. Klein, Clin. Chem. 38, 1613 (1992)). Biosensors are electrochemical devices with enzymes immobilized at the surface of an electrochemical transducer.
Minimally Invasive Glucose Measurement
Portable, xe2x80x9cminimally-invasivexe2x80x9d testing systems are now commercially available. These systems require the patient to stick themselves to obtain a drop of blood which is then applied to a disposable test strip containing coated reagents or an electrochemical test element.
Although the portable instruments that read the strips are relatively inexpensive ($100-$200), the cumulative cost to diabetics for the disposable strips is considerable. Compliance is another major problem for minimally invasive techniques. Frequent finger sticks are painful and can result in infections, scarring, and nerve damage in the finger. Disposal of potentially biohazardous test strips is yet another problem with this method.
Noninvasive Glucose Measurement
xe2x80x9cNoninvasivexe2x80x9d (NI) glucose sensing techniques measure in-vivo glucose concentrations without collecting a blood sample. As defined herein, a xe2x80x9cnoninvasivexe2x80x9d apparatus or method is one which can be used without removing a sample from, or without inserting any instrumentation into, the tissues. The concept involves irradiating a vascular region of the body with electromagnetic radiation and measuring the spectral information that results from one of four primary processes: reflection, absorption, scattering, or emission. The extent to which each of these processes occurs is dependent upon a variety of factors, including the wavelength and polarization state of the incident radiation and the glucose concentration in the body part. Glucose concentrations are determined from the spectral information by comparing the measured spectra to a calibration curve or by reference to a physical model of the tissue under examination. A brief description of noninvasive glucose measurements in the prior art is provided below.
Description of the Art
Infrared
NI techniques that utilize the absorption of infrared radiation can be divided into three distinct wavelength regimes: Near-infrared (NIR), Mid-infrared (MIR) and Far-infrared (FIR). As defined herein, NIR involves the wavelength range of from about 600 nm to about 1200 nm, MIR involves the wavelength range of from about 1200 nm to about 3000 nm, and FIR involves the wavelength range of from about 3000 nm to about 25000 nm. As defined herein, xe2x80x9cInfraredxe2x80x9d (or IR) is taken to mean a range of wavelengths from about 600 nm to about 25000 nm.
NIR
U.S. Pat. Nos. 5,086,229, 5,324,979, 5,237,178 describe a number of noninvasive NIR instruments and methods for measuring blood glucose. In general, a blood-containing body part (e. g., a finger) is illuminated by one or more light sources and the light that is transmitted through the body part is detected by one or more detectors. A glucose level is derived from a comparison to reference spectra for glucose and background interferants.
MIR
The use of MIR radiation for NI glucose measurement has been described in U.S. Pat. Nos. 5,362,966, 5,237,178, 5,533,509, 4,655,225. The principles of operation are similar to those described for the NIR, except that the penetration depth of the MIR light is less than that for NIR. As a consequence, most measurements in this region have been performed using a backscattering geometry. As defined herein, a xe2x80x9cbackscattering geometryxe2x80x9d describes a configuration wherein scattered radiation is collected on the same side of the sample as the entry point of the incident radiation. A xe2x80x9ctransmission geometryxe2x80x9d describes a configuration wherein light is transmitted through the sample and collected on the opposite side of the sample as the entry point of the incident radiation.
FIR
FIR measurements have been described in U.S. Pat. Nos. 5,313,941, 5,115,133, 5,481,113, 5,452,716, 5,515,847, 5,348,003, and DE 4242083.
Photoacoustic Spectroscopy
As will be described more thoroughly below, the photoacoustic (PA) effect results from the absorption of a pulse of optical energy, which is rapidly converted into thermal energy. The subsequent thermal expansion generates an acoustic pressure wave, which is measured by an acoustic transducer. In addition to the absorption of light, the measured PA signal depends upon the speed of sound in the medium, the thermal expansion coefficient of the analyte, and the specific heat of the medium.
Glucose measurements employing the photoacoustic effect have been described by Quan et al. (K. M. Quan, G. B. Christison, H. A. MacKenzie, P. Hodgson, Phys. Med. Biol., 38 (1993), pp. 1911-1922) and U.S. Pat. No. 5,348,002.
Caro et al. (U.S. Pat. No. 5,348,002) provides a PA detector and an optical detector; however, the device and method of Caro require that a relationship be drawn between the xe2x80x9cphotoacoustic response and the degree of absorptionxe2x80x9d of the sample. As will be described more fully below, the present invention requires no such a priori information. Rather, it is based solely upon a correlation between the measured PA signal and the analyte concentration. Further, the present invention employs focusing optics in order to generate a more concentrated PA signal than the apparatus of Caro et al., which employs the diverging output of an optical fiber for photoexcitation. As a result, the present invention is more sensitive and more efficient in its operation than are the device and method of Caro.
Scattering
As defined herein xe2x80x9cscatteringxe2x80x9d includes Rayleigh, Mie, and Raman scattering. Glucose decreases the intensity of Mie scattering by decreasing the refractive index difference between the extracellular fluid (ECF) and cell membranes. Gratton et al. (U.S. Pat. No. 5,497,769) have proposed a sensor based upon this effect; however, the signal to noise ratio for this technique is expected to be inadequate for glucose measurement.
Raman Scattering
U.S. Pat. No. 5,553,616 teaches the use of Raman scattering with excitation in the near infrared (780 nm) and an artificial neural network for measuring blood glucose. Glucose Raman bands that are distinct from protein Raman bands may be chosen, however, the sensitivity of this method limits its applicability for in-vivo measurements. WO 92/10131 discusses the application of stimulated Raman spectroscopy for detecting the presence of glucose.
Polarimetry
Methods for the determination of glucose concentrations using changes in the polarization of light are described in International Patent Publications WO 92/10131, WO 93/07801, WO 94/02837, WO 94/05984, and WO 94/13199 and U.S. Pat. Nos. 4,882,492, 5,086,229, 5,209,231, 5,218,207, 5,321,265, 5,337,745, 5,361,758, and 5,383,452.
Emission
As used herein, xe2x80x9cemissionxe2x80x9d measurements are defined as measurements of fluorescence or phosphorescence. Emission spectroscopic measurements have been described in U.S. Pat. Nos. 5,341,805, 5,383,452, 5,626,134 and 5,628,310, and 5,582,168.
Challenges for NI Glucose Measurement
The NI techniques listed above are painless, reagentless, and are less expensive than the finger stick approach over the life of the patient. NI testing also eliminates the potentially biohazardous waste associated with invasive and minimally invasive measurements. However, NI methods have not yet achieved the level of accuracy and precision that is required for measuring physiologically relevant glucose concentrations in-vivo.
A major challenge for all of the noninvasive techniques to date has been to collect spectral information with sufficiently high signal-to-noise ratios to discriminate weak glucose signals from the underlying noise. In the ideal case, a noninvasive sensor would be highly sensitive for the parameter of interest (e. g., glucose concentration) while remaining insensitive to interfering analytes or physiological parameters. In practice, all of the noninvasive measurement techniques described in the prior art are sensitive to one or more interfering xe2x80x9cphysiologicalxe2x80x9d or xe2x80x9cspectralxe2x80x9d variables.
Physiological and Spectral Variables
As used herein, the term xe2x80x9cphysiological variablesxe2x80x9d describes physiological parameters, such as temperature or pulsatile blood flow, that can adversely affect the sensitivity or selectivity of a noninvasive measurement. Examples of several important physiological variables are listed in Table 1 below. As used herein, the term xe2x80x9cspectral variablesxe2x80x9d describes spectral features that arise either from poorly resolved analyte bands or from other interfering components in the sample. Several significant sources of spectral interference in biological samples such as water, hemoglobin, albumin, cholesterol, urea, and fat are listed in Table 2 below. Other tissue constituents that are present at lower concentrations or have lower absorption cross-sections may also contribute to an overall background signal that is difficult to subtract.
Physiological and spectral variables can introduce unwanted noise, or worse, completely overwhelm the measured signals of interest (e. g., those related to glucose concentration). It is difficult to eliminate these interferences because they may exhibit one or more of the following properties:
(a) they may contribute nonlinearly to the measured signal,
(b) they may vary with spatial location within the sample,
(c) they may vary over time, or
(d) they may vary from sample to sample.
Examples of (a) nonlinear, (b) spatial, (c) temporal, and (d) sample-dependent interferences are briefly described below.
(a) Nonlinear Contributions
A change in temperature can have a nonlinear effect on the infrared spectrum by altering the intensities as well as the frequencies of the dominant water absorption bands. A temperature change will also modify the refractive index of the sample which, in turn, will alter the scattering properties of the sample. The effective optical path length will change as a result of the aforementioned change in scattering properties. Thus, physiological and spectral parameters are often inseparably linked and a change in one of these variables can modulate the impact of other interfering variables. The result is a nonlinear change in the measured signal for a linear change in one of the physiological or spectral variables.
(b) Inhomogeneous Distributions
Physiological or spectral variables can also vary over one or more spatial dimensions of the sample. Human skin, for example, is an important obstacle for noninvasive measurements because of its multilayered, three-dimensional architecture. Human skin comprises the stratum corneum, the epidermis, and the dermis. Biological chromophores (spectral variables) may be confined to a single layer or may be evenly distributed among multiple layers. Melanin, for example, is distributed between the epidermis and stratum corneum, whereas the various forms of hemoglobin are confined to vessels of the dermis, and only indirectly exert any influence on the optical properties of the overlying epidermis.
(c) Time Varying Contributions
Referring again to Tables 1 and 2, each of the physiological and spectral variables may fluctuate over time and each variable may oscillate at a different frequency. Although the mechanisms governing the modulation of the spectral and physiological variables listed in Tables 1 and 2 are not yet fully understood, the frequencies of oscillation are predictable, or at least measurable. A few representative examples are described below.
Tissue perfusion (and consequently tissue temperature) can fluctuate for a variety of reasons, including local infections, inflammation, and some malignancies. A familiar example is the change in skin coloration, which can accompany exercise, alcohol intake, or even a change in position from sitting to standing.
On a longer time scale, the physical properties of human skin change as a normal function of aging. These changes include decreased solubility (Schnider, S. L., and Kohn, R. R., J. Clin. Invest. 67, (1981) pp.1630-1635), decreased proteolytic digestibility (Hamlin, C. R., Luschin, J. H., and Kohn, R. R., Exp. Gerontol. 13, (1978) pp. 415-523), increased heat denaturation time (Snowden, J. M., Eyre, D. R., and Swann, D. H., Biochem. Biophys. Acta, 706, (1982) pp. 153-157), and the accumulation of yellow and fluorescent materials (LaBella, F. S., and Paul, G., J. Gerontol., 20, (1964) pp. 54-59). These changes appear to be accelerated in diabetes, and may alter the scattering properties of the skin via the formation of intermolecular crosslinks between collagen fibrils.
(d) Sample to Sample Variability
The influence of physiological and spectral variables may differ from individual to individual or between measurements, thereby leading to irreproducible results. As mentioned previously, individual differences in the optical properties of skin such as those due to aging or race (melanin content) can dramatically affect noninvasive measurements.
Signal Processing
In an attempt to selectively extract glucose-dependent information in the presence of dominating signals from the physiological and spectral variables described above, skilled artisans in the field have applied a variety of sophisticated mathematical algorithms. These have included principal components regression (PCR), partial least squares (PLS), and artificial neural networks (ANN), among others. The results of signal processing, however, are highly dependent upon the quality of the starting data. PLS and ANN algorithms are powerful techniques for correlating minute spectral variations with analyte concentration. However, these methods are also sensitive to time-varying fluctuations in physiological and spectral variables that happen to correlate with changes in analyte concentration. Without adequate compensation for the effects of physiological and spectral variables, PLS and ANN algorithms can highlight such correlations and provide misleading results.
State of the Art
Thus, despite the variety of spectroscopic techniques employed and the advanced signal processing algorithms used for data manipulation, there is still no commercially available device that provides noninvasive glucose measurements with a sensitivity that is comparable to the invasive methods. All of the prior art methods respond to glucose concentrations, but they are also sensitive to physiological and spectral variables. As a result, current approaches to non-invasive glucose testing have not achieved acceptable precision and accuracy.
Thus, there is a continuing need for improved noninvasive analytical instruments and methods that will provide essentially the same accuracy as conventional, invasive blood glucose tests. There is also a need for noninvasive, low-cost methods and instruments for the measurement of glucose levels in diabetic or hypoglycemic patients. There is also a need for a durable, cost-effective, reagent-free, painless, and environmentally friendly apparatus for measuring blood glucose.
The present invention solves a fundamental problem that has plagued noninvasive measurements in the prior art. Namely, for any given noninvasive measurement performed on a biological sample, multiple physiological and spectral variables can interfere with the measurement of the parameter(s) of interest (e. g., the concentration of an analyte, such as glucose). As described above, physiological and spectral interferences are difficult to remove because they can exhibit any or all of the following properties:
(a) they may contribute nonlinearly to the measured signal,
(b) they may vary with spatial location within the sample,
(c) they may vary over time, or
(d) they may vary from sample to sample.
As will be described more fully below, the present invention measures the reflected, scattered, absorbed, emitted, or transmitted light as a function of multiple dimensions. As defined herein, a xe2x80x9cdimensionxe2x80x9d is a measured quantity. It can be related to light which is reflected, scattered, absorbed, emitted, or transmitted by the sample. It can also be related to time or space or both.
For example, a spectral dimension might comprise the wavelength of light absorbed by the sample, the polarization state of light entering or exiting the sample, the angle of incidence of light entering or exiting the sample, a difference between the frequencies (or wavelengths) of light entering and exiting the sample, a difference between the polarization states of light entering and exiting the sample, the angle between the light entering and exiting the sample, or some other observable spectral property.
A temporal dimension might include, for example, the duration of time between the entry of light into the sample and the exit of light from the sample, the duration of time between the entry of light into the sample and the detection of a measured spectroscopic signal (e. g., acoustic energy), the duration of time between spectroscopic measurements, an oscillation frequency of the sample, an oscillation frequency of the spectroscopic measurement or some other variable which is measurable in the time or frequency domain.
A spatial dimension might include, for example, a distance along one or more Cartesian or polar coordinates such as a separation distance between two or more points in the sample, the size of a constituent of the sample (e. g., a particle size), the distance or angle between a detector and the sample, the effective optical path length in the sample, or a spatial frequency of the sample.
In the present invention, physiological and spectral interferences are measured over multiple dimensions so that their contributions may be separated, quantified, and removed from the signals of interest (e. g., those related to the concentration of an analyte, such as glucose). A multivariate algorithm is employed to selectively extract parameters of interest from the measured signals.
In one embodiment, the present invention comprises a multiplex sensor and a method of use that provides enhanced selectivity and sensitivity. In this method, one or more parameters of the sample are measured by means of multiple spectroscopic techniques, and the interferences from physiological and spectral variables are reduced or eliminated.
Another embodiment of the present invention comprises a multiplex sensor and a method of use that provides enhanced selectivity and sensitivity. One or more parameters of the sample are measured by means of at least two different spectroscopic techniques, wherein the at least two different spectroscopic techniques are selected from the group consisting of:
(a) infrared absorbance
(b) scattering
(c) emission
(d) polarization, and
(e) photoacoustics
Weaknesses or interferences present in the measurements from one spectroscopic technique are compensated by a different technique.
Another embodiment of the present invention comprises an apparatus and method for measuring one or more parameters of a sample (e. g., the presence or concentration of one or more analytes) by means of at least two spectroscopic techniques selected from different members of the group consisting of:
(a) infrared absorbance
(b) scattering
(c) emission
(d) polarization, and
(e) photoacoustics
wherein the measurements are recorded as a function of at least one spatial dimension.
Another embodiment of the present invention comprises an apparatus and method for measuring one or more parameters of a sample (e. g., the presence or concentration of one or more analytes) by means of at least two spectroscopic techniques selected from different members of the group consisting of:
(a) infrared absorbance
(b) scattering
(c) emission
(d) polarization, and
(e) photoacoustics
wherein the measurements are recorded as a function of at least one temporal dimension.
Another embodiment of the present invention comprises an apparatus and method for measuring one or more parameters of a sample (e. g., the presence or concentration of one or more analytes) by means of at least two spectroscopic techniques selected from different members of the group consisting of:
(a) infrared absorbance
(b) scattering
(c) emission
(d) polarization, and
(e) photoacoustics
wherein the measurements are recorded as a function of at least one spatial dimension and at least one temporal dimension.
Another embodiment of the present invention provides enhanced selectivity by illuminating the sample with electromagnetic radiation and recording the intensity of the reflected, absorbed, scattered, emitted or transmitted radiation as a function of at least three dimensions wherein the at least three dimensions are selected from the group consisting of:
(a) spectral dimensions,
(b) temporal dimensions, and
(c) spatial dimensions.
and wherein at least two of the at least three dimensions are spectral dimensions. Preferably, at least three of the at least three dimensions are spectral dimensions.
Another embodiment of the present invention comprises an apparatus and method for making multiple, consecutive measurements of at least one parameter of a sample (e. g., the presence or concentration of one or more analytes) by means of at least two spectroscopic techniques selected from different members of the group consisting of:
(a) infrared absorbance
(b) scattering
(c) emission
(d) polarization
(e) photoacoustics
Another embodiment of the present invention comprises a multiplex sensor and a method of use that provides enhanced selectivity and sensitivity. One or more parameters of the sample are measured by means of at least three different spectroscopic techniques, wherein said at least three different spectroscopic techniques are selected from the group consisting of:
(a) infrared absorbance
(b) scattering
(c) emission
(d) polarization, and
(e) photoacoustics
In another embodiment, an improved apparatus and method are provided for measuring the presence or concentration of one or more analytes (e. g., glucose, alcohol, blood urea nitrogen, bilirubin, hemoglobin, creatine, electrolytes, blood gases, cholesterol, hormones or drugs of abuse) in a sample.
The present invention is particularly advantageous for biological samples where multiple interfering analytes or physiological variables can affect the measurement. The sample may be obtained using invasive or minimally invasive means. Alternatively, noninvasive measurements may be made on a body part of a patient, e. g., a finger, earlobe, lip, toe, skin fold, or bridge of the nose.